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VideoResearcher achieves state-of-the-art performance among self-improving agents and approaches the human-designed upper bound, demonstrating a training-free paradigm for long-video understanding that expands agent capabilities through autonomous tool development while reducing costly manual engineering.
Focusing on relevant clue intervals can significantly boost long-video understanding accuracy while reducing the input frame burden on models.
